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Better prediction of clinical outcome in clear cell renal cell carcinoma based on a 6 metabolism-related gene signature
It has been reported that metabolic disorders participate in the formation and progression of clear cell renal cell carcinoma (ccRCC). However, the predictive value of metabolism-related genes (MRGs) in clinical outcome of ccRCC is still largely unknown. Herein, a novel metabolism-related signature...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10352344/ https://www.ncbi.nlm.nih.gov/pubmed/37460577 http://dx.doi.org/10.1038/s41598-023-38380-7 |
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author | Yu, Zhixian Zhan, Yating Guo, Yong He, Dalin |
author_facet | Yu, Zhixian Zhan, Yating Guo, Yong He, Dalin |
author_sort | Yu, Zhixian |
collection | PubMed |
description | It has been reported that metabolic disorders participate in the formation and progression of clear cell renal cell carcinoma (ccRCC). However, the predictive value of metabolism-related genes (MRGs) in clinical outcome of ccRCC is still largely unknown. Herein, a novel metabolism-related signature was generated to assess the effect of MRGs on the prognosis of ccRCC patients. Important module MRGs were selected by differentially expressed analysis and WGCNA. Subsequently, the hub MRGs were screened via univariate cox regression as well as LASSO regression. A new metabolism-related signature of 6 hub MRGs (PAFAH2, ACADSB, ACADM, HADH, PYCR1 and ITPKA) was constructed, with a good prognostic prediction ability in the TCGA cohort. The prediction accuracy of this signature was further confirmed in both GSE22541 and FAHWMU cohort. Interestingly, this MRG risk signature was highly correlated with tumor mutation burden and immune infiltration in ccRCC. Notably, lower PAFAH2, a member of 6 MRGs, was found in ccRCC. Knockdown of PAFAH2 contributed to renal cancer cell proliferation and migration. Collectively, a 6-MRG prognostic risk signature is generated to estimate the prognostic status of ccRCC patients, providing a novel insight in the prognosis prediction and treatment of ccRCC. |
format | Online Article Text |
id | pubmed-10352344 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-103523442023-07-19 Better prediction of clinical outcome in clear cell renal cell carcinoma based on a 6 metabolism-related gene signature Yu, Zhixian Zhan, Yating Guo, Yong He, Dalin Sci Rep Article It has been reported that metabolic disorders participate in the formation and progression of clear cell renal cell carcinoma (ccRCC). However, the predictive value of metabolism-related genes (MRGs) in clinical outcome of ccRCC is still largely unknown. Herein, a novel metabolism-related signature was generated to assess the effect of MRGs on the prognosis of ccRCC patients. Important module MRGs were selected by differentially expressed analysis and WGCNA. Subsequently, the hub MRGs were screened via univariate cox regression as well as LASSO regression. A new metabolism-related signature of 6 hub MRGs (PAFAH2, ACADSB, ACADM, HADH, PYCR1 and ITPKA) was constructed, with a good prognostic prediction ability in the TCGA cohort. The prediction accuracy of this signature was further confirmed in both GSE22541 and FAHWMU cohort. Interestingly, this MRG risk signature was highly correlated with tumor mutation burden and immune infiltration in ccRCC. Notably, lower PAFAH2, a member of 6 MRGs, was found in ccRCC. Knockdown of PAFAH2 contributed to renal cancer cell proliferation and migration. Collectively, a 6-MRG prognostic risk signature is generated to estimate the prognostic status of ccRCC patients, providing a novel insight in the prognosis prediction and treatment of ccRCC. Nature Publishing Group UK 2023-07-17 /pmc/articles/PMC10352344/ /pubmed/37460577 http://dx.doi.org/10.1038/s41598-023-38380-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Yu, Zhixian Zhan, Yating Guo, Yong He, Dalin Better prediction of clinical outcome in clear cell renal cell carcinoma based on a 6 metabolism-related gene signature |
title | Better prediction of clinical outcome in clear cell renal cell carcinoma based on a 6 metabolism-related gene signature |
title_full | Better prediction of clinical outcome in clear cell renal cell carcinoma based on a 6 metabolism-related gene signature |
title_fullStr | Better prediction of clinical outcome in clear cell renal cell carcinoma based on a 6 metabolism-related gene signature |
title_full_unstemmed | Better prediction of clinical outcome in clear cell renal cell carcinoma based on a 6 metabolism-related gene signature |
title_short | Better prediction of clinical outcome in clear cell renal cell carcinoma based on a 6 metabolism-related gene signature |
title_sort | better prediction of clinical outcome in clear cell renal cell carcinoma based on a 6 metabolism-related gene signature |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10352344/ https://www.ncbi.nlm.nih.gov/pubmed/37460577 http://dx.doi.org/10.1038/s41598-023-38380-7 |
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